Improving Quantitative Laboratory Analysis of Phycobiliproteins to Provide High Quality Validation Data for Ocean Color Remote Sensing Algorithm

Identification and characterization of phytoplankton communities and their physiology is a primary aim of NASA's PACE satellite mission. The concentration and composition of phytoplankton pigments modulate the spectral distribution of light emanating from the ocean, which is measured by ocean color satellites, and thus provide critical information on phytoplankton community composition and physiological parameters. One diagnostic class of pigments not routinely well-characterized is the phycobiliproteins (PBPs), and NASA has a requirement to collect and distribute high quality in situ data in support of data product validation activities for ocean color missions. Phycobiliproteins are light-harvesting proteins that are the predominant photosynthetic pigments in some classes of phytoplankton including cyanobacteria, such as Synechococcus, Trichodesmium, and Microcystis. With the advance of hyperspectral ocean color sensors such as on PACE (expected to launch in late 2022), it is essential that we implement routine analysis of PBPs that satisfies several considerations: reproducible, high extraction efficiency for a variety of environments, and Suitable for large scale analysis. Published techniques for PBP analysis vary in recommendations for: collection, extraction, disruption mode, and analysis; evidence suggests the variation in results may depend at least in part on the species and even strain(s) of interest. Experiments that tested variations in these parameters have drawn very different conclusions regarding extraction efficiency and reproducibility. Cyanobacteria are more difficult to extract than other PBP-containing algae such as cryptophytes, but can be important primary producers. We used a cryptophyte (Rhodomonas salina) and cyanobacterium (Synechococcus sp.) to compare extraction efficiencies of water samples concentrated via centrifugation to filtered samples using two different extraction buffers (phosphate and asolectin-CHAPS). Samples were analyzed on a fluorometer configured for PC and PE detection. The results have important implications for collection and storage of samples for routine analysis; some previous studies (although not all) have suggested that filtered samples have a much lower extraction efficiency than whole water samples

Plasma kisspeptin levels are associated with insulin secretion in nondiabetic individuals

To evaluate if plasma kisspeptin concentrations are associated with insulin secretion, as suggested by recent in vitro studies, independently of confounders. 261 nondiabetic subjects were stratified into tertiles according to kisspeptin values. Insulin secretion was assessed using indexes derived from oral glucose tolerance test (OGTT). After adjusting for age, gender, and BMI, subjects in the highest (tertile 3) kisspeptin group exhibited significantly lower values of insulinogenic index, corrected insulin response (CIR30), and Stumvoll indexes for first-phase and second-phase insulin release as compared with low (tertile 1) or intermediate (tertile 2) kisspeptin groups. Univariate correlations between kisspeptin concentration and metabolic variables showed that kisspeptin concentration was significantly and positively correlated with age, blood pressure, and 2-h post-load glucose, and inversely correlated with BMI, and waist circumference. There was an inverse relationship between kisspeptin levels and OGTT-derived indexes of glucose-stimulated insulin secretion. A multivariable regression analysis in a model including all the variables significantly correlated with kisspeptin concentration showed thar age (β = -0.338, P<0.0001), BMI (β = 0.272, P<0.0001), 2-h post-load glucose (β = -0.229, P<0.0001), and kisspeptin (β = -0.105, P = 0.03) remained associated with insulinogenic index. These factors explained 34.6% of the variance of the insulinogenic index. In conclusion, kisspeptin concentrations are associated with insulin secretion independently of important determinants of glucose homeostasis such as gender, age, adiposity, 2-h post-load glucose, and insulin sensitivity

Insulin-like growth factor-1 is a negative modulator of glucagon secretion

Glucagon secretion involves a combination of paracrine, autocrine, hormonal, and autonomic neural mechanisms. Type 2 diabetes often presents impaired glucagon suppression by insulin and glucose. Insulin-like growth factor-I (IGF-1) has elevated homology with insulin, and regulates pancreatic β-cells insulin secretion. Insulin and IGF-1 receptors share considerable structure homology and function. We hypothesized the existence of a mechanism linking the inhibition of α-cells glucagon secretion to IGF-1. Herein, we evaluated the association between plasma IGF-1 and glucagon levels in 116 nondiabetic adults. After adjusting for age gender and BMI, fasting glucagon levels were positively correlated with 2-h post-load glycaemia, HOMA index and fasting insulin, and were negatively correlated with IGF-1 levels. In a multivariable regression, the variables independently associated to fasting glucagon were circulating IGF-1 levels, HOMA index and BMI, explaining 20.7% variation. To unravel the molecular mechanisms beneath IGF-1 and glucagon association, we investigated whether IGF-1 directly modulates glucagon expression and secretion in an in vitro model of α-cells. Our data showed that IGF-1 inhibits the ability of low glucose concentration to stimulate glucagon expression and secretion via activation of the phosphatidylinositol-3-kinase/Akt/FoxO1 pathway. Collectively, our results suggest a new regulatory role of IGF-1 on α-cells biological function

Geostationary Coastal and Air Pollution Events (GEO CAPE) Instrument Performance Study

The Ultimate objective of the GEO-CAPE 2014 study: Quantify the cost impact of very specific changes in instrument performance! The customer has defined 4 instrument types they are notionally interested in:! FR: Filter Radiometer! WAS: Wide Angle Spectrometer! MSS: Multi Slit Spectrometer! SSS: Single Slit Spectrometer

The Effects of Non-Indigenous Macrophytes on Native Biodiversity: Case Studies from Sicily

Biological invasions are widely recognized as a major threat to native biodiversity, ecosys tem functioning and services. Non-indigenous species (NIS) may in time become invasive (invasive alien species (IAS)), determining significant environmental, socioeconomic and human health impacts such as biodiversity loss and ecosystem service degradation. The Mediterranean islands, particu larly Sicily and the circum-Sicilian islands (northwestern Mediterranean Sea), which are important hotspots of biodiversity, are notably vulnerable to anthropogenic pressures such as biological in vasions. Therefore, monitoring NIS distribution as well as understanding their effects on native biodiversity is critical in these areas for planning effective conservation strategies. Here, we report four different case studies from Sicily that highlight how NIS may affect native biodiversity and habitats. The first three case studies were carried out within Marine Protected Areas (MPAs) and highlight (1) the ability of Caulerpa cylindracea to promote the establishment of other NIS, including biofouling worms belonging to the genus Branchiomma; (2) how the shift in habitat from the native Ericaria brachycarpa to the invasive Asparagopsis taxiformis may drastically erode the primary producer biomass and associated biodiversity; and (2) that the presence of Lophocladia lallemandii can affect the molluscan assemblage inhabiting the canopy-forming Gongolaria montagnei. The fourth case study, performed along the northwestern coast of Sicily, shows how Halophila stipulacea can affect the growth of the co-occurring native seagrass Cymodocea nodosa. Overall, these case studies demonstrate various ways in which NIS can interact with native biodiversity and habitats. Furthermore, they emphasize that MPAs are ineffective at preventing the introduction and spread of NIS

Eastern U.S. Continental Shelf Carbon Budget: Integrating Models,Data Assimilation, and Analysis

The U.S. East Coast Continental Shelf (USECoS) project was initiated in 2004 with the overall goal of developing carbon budgets for Mid-Atlantic and South Atlantic regions of the eastern U.S. coast. We addressed this goal through a series of specific research questions that were designed to understand carbon inputs and fates in the two regions, dominant food web pathways for carbon cycling, and similarities/differences in carbon cycling in the two continental shelf systems. The USECoS project represents a major effort to simultaneously synthesize and integrate diverse data sets, field measurements, models, and modeling approaches. We expect that the type of approach taken here will result in more insight than would be possible if each component of the program moved forward independently. The primary significance of this project is in providing a strong quantitative basis for the development of future observational and modeling studies of carbon budgets of continental shelf systems. A strong aspect of the USECoS project is the integration of modeling and extensive physical, chemical, and biological data sets, which provides an opportunity for modeling and data analyses to inform one another from the outset. This research is particularly germane to NASA's carbon cycle research focus and coastal research initiative and the U.S. Climate Change Research Program, all of which support the goals of the North American Carbon Program. We highlight primary approaches that have been used, and some of the challenges and results that have come from interactions among our team of investigators. The global scale and interdisciplinary nature of the science questions that we now face in Earth Science are such that integrated teams of investigators are needed to address them

Different Types of Housing and Respiratory Health Outcomes

Evidence has shown that housing conditions may substantially influence the health of residents. Different types of housing have different structures and construction materials, which may affect indoor environment and housing conditions. This study aimed to investigate whether people living in different types of housing have different respiratory health outcomes. The data from the 1999–2006 National Health and Nutrition Examination Survey were used for the analyses. The types of housing included houses, townhouses, apartments, and mobile homes. Respiratory symptoms included wheezing, coughing, sputum, and dyspnea; respiratory diseases included asthma, chronic bronchitis, emphysema, and chronic obstructive pulmonary disease (COPD). Multiple logistic regression was used to calculate odds ratio (OR) and 95% confidence interval (CI) after adjustment for potential confounding factors. A total of 11,785 participants aged 40 years and older were included in the analyses. Compared with those living in single family houses, participants living in mobile homes were more likely to have respiratory conditions, the OR (95% CI) was 1.38 (1.13–1.69) for wheezing, and 1.49 (1.25–1.78) for dyspnea; whereas participants living in apartments were less likely to have respiratory conditions, the OR (95% CI) was 0.58 (0.36–0.91) for chronic bronchitis, and 0.69 (0.49–0.97) for COPD. Compared with living in single family houses, living in mobile home was associated with worse, whereas living in apartments was associated with better, respiratory health outcomes. Further research is needed to better understand the underlying mechanisms and prevent adverse respiratory effects associated with living in mobile homes

Homogeneous Photometry V: The Globular Cluster NGC 4147

New BVRI broad-band photometry and astrometry are presented for the globular cluster NGC 4147, based upon measurements derived from 524 ground-based CCD images mostly either donated by colleagues or retrieved from public archives. We have also reanalysed five exposures of the cluster obtained with WFPC2 on the Hubble Space Telescope in the F439W and F555W (B and V) filters. We present calibrated color-magnitude and color-color diagrams. Analysis of the color-magnitude diagram reveals morphogical properties generally consistent with published metal-abundance estimates for the cluster, and an age typical of other Galactic globular clusters of similar metallicity. We have also redetermined the periods and mean magnitudes for the RR Lyrae variables, including a new c-type variable reported here for the first time. Our data do not show clear evidence for photometric variability in candidate V18, recently reported by Arellano Ferro et al. (2004). These observations also support the non-variable status of candidates V5, V9, and V15. The union of our light-curve data with those of Newburn (1957), Mannino (1957) and Arellano Ferro et al. (op. cit.) permits the derivation of significantly improved periods. The mean periods and the Bailey period-amplitude diagrams support the classification of the cluster as Oosterhoff I despite its predominantly blue horizontal branch. The number ratio of c- to ab-type RR Lyrae stars, on the other hand, is unusually high for an Oosterhoff I cluster. The calibrated results have been made available through the first author's web site.Comment: 30 pages, 30 figures. PASP, in press. Uses 11/2004 version of emulateapj (included). For the full-resolution preprint, the reader is encouraged to download the ps file (123 pages, manuscript format) available at http://cadcwww.hia.nrc.ca/stetson/NGC4147/ms.ps.gz, or the pdf file (30 pages, preprint format) available at http://www.astro.puc.cl/~mcatelan/N4147/full-res.pd

Association between serum Mg2+ concentrations and cardiovascular organ damage in a cohort of adult subjects

Magnesium (Mg2+) levels are associated with insulin resistance, hypertension, atherosclerosis, and type 2 diabetes (T2DM). We evaluated the clinical utility of physiological Mg2+ in assessing subclinical cardiovascular organ damage including increased carotid artery intima-media thickness (c-IMT) and left ventricular mass index (LVMI) in a cohort of well-characterized adult non-diabetic individuals. Age-and gender-adjusted correlations between Mg2+ and metabolic parameters showed that Mg2+ circulating levels were correlated negatively with body mass index (BMI), fasting glucose, and 2h-oral glucose tolerance test (OGTT) glucose. Similarly, Mg2+ levels were significantly and negatively related to c-IMT and LVMI. A multivariate regression analysis revealed that age (β = 0.440; p < 0.0001), BMI (β = 0.225; p < 0.0001), and Mg2+ concentration (β = −0.122; p < 0.01) were independently associated with c-IMT. Age (β = 0.244; p = 0.012), Mg2+ (β = −0.177; p = 0.019), and diastolic blood pressure (β = 0.184; p = 0.038) were significantly associated with LVMI in women, while age (β = 0.211; p = 0.019), Mg2+ (β = −0.171; p = 0.038) and the homeostasis model assessment index of insulin resistance (HOMA-IR) (β = −0.211; p = 0.041) were the sole variables associated with LVMI in men. In conclusion, our data support the hypothesis that the assessment of Mg2+ as part of the initial work-up might help unravel the presence of subclinical organ damage in subjects at increased risk of cardiovascular complications